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Add examples for frozenlake and emailsearch (#94)

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Yuchang Sun
2026-01-19 12:25:13 +08:00
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parent 3821fb04ac
commit 654c35127a
26 changed files with 3370 additions and 14 deletions
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6
tuner/math_agent/README.md
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@@ -248,10 +248,10 @@ if __name__ == "__main__":
Here, we use `DatasetConfig` to load the training dataset, `TunerModelConfig` to initialize the trainable model, and `AlgorithmConfig` to specify the RL algorithm and its hyperparameters.
> Note:
> The `tune` function is based on [Trinity-RFT](https://github.com/modelscope/Trinity-RFT) and it converts the input parameters into a YAML configuration internally.
> The `tune` function is based on [Trinity-RFT](https://github.com/agentscope-ai/Trinity-RFT) and it converts the input parameters into a YAML configuration internally.
> Advanced users can ignore `model`, `train_dataset`, `algorithm` arguments and provide a configuration file path pointing to a YAML file using the `config_path` argument instead (see [config.yaml](./config.yaml) for an example).
> We recommend using the configuration file approach for fine-grained control over the training process and leveraging advanced features provided by Trinity-RFT.
> You can refer to the Trinity-RFT [Configuration Guide](https://modelscope.github.io/Trinity-RFT/en/main/tutorial/trinity_configs.html) for more details on configuration options.
> You can refer to the Trinity-RFT [Configuration Guide](https://agentscope-ai.github.io/Trinity-RFT/en/main/tutorial/trinity_configs.html) for more details on configuration options.
The checkpoint and logs will automatically be saved to the `checkpoints/AgentScope` directory under the current working directory and each run will be saved in a sub-directory suffixed with the current timestamp.
You can find the tensorboard logs inside `monitor/tensorboard` of the checkpoint directory.
@@ -342,7 +342,7 @@ After implementing the workflow function, follow these steps to run the training
- At least 2 NVIDIA GPUs with CUDA 12.8 or newer.
- Adjust the configuration file ([config.yaml](./config.yaml)) based on your hardware.
- Follow the Trinity-RFT [installation guide](https://modelscope.github.io/Trinity-RFT/en/main/tutorial/trinity_installation.html) to install the latest version from source code.
- Follow the Trinity-RFT [installation guide](https://agentscope-ai.github.io/Trinity-RFT/en/main/tutorial/trinity_installation.html) to install the latest version from source code.
- Download the GSM8K dataset and Qwen/Qwen3-0.6B model checkpoints (example):
```bash

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tuner/math_agent/README_zh.md
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@@ -245,10 +245,10 @@ if __name__ == "__main__":
这里用 `DatasetConfig` 加载训练数据集，`TunerModelConfig` 初始化可训练模型，`AlgorithmConfig` 指定 RL 算法及其超参数。
> 注意：
> `tune` 函数基于 [Trinity-RFT](https://github.com/modelscope/Trinity-RFT) 实现，会将输入参数自动转为 YAML 配置。
> `tune` 函数基于 [Trinity-RFT](https://github.com/agentscope-ai/Trinity-RFT) 实现，会将输入参数自动转为 YAML 配置。
> 高级用户可忽略 `model`、`train_dataset`、`algorithm` 参数，直接用 `config_path` 指定 YAML 配置文件（见 [config.yaml](./config.yaml) 示例）。
> 推荐用配置文件方式实现更细粒度的训练控制，充分利用 Trinity-RFT 的高级特性。
> 详细配置说明见 Trinity-RFT [配置指南](https://modelscope.github.io/Trinity-RFT/zh/main/tutorial/trinity_configs.html)。
> 详细配置说明见 Trinity-RFT [配置指南](https://agentscope-ai.github.io/Trinity-RFT/zh/main/tutorial/trinity_configs.html)。
训练产生的 checkpoint 和日志信息会自动保存在当前目录下的 `checkpoints/AgentScope` 中，每次运行会新建带时间戳的子目录。
TensorBoard 日志在 checkpoint 目录下的 `monitor/tensorboard` 中。
@@ -335,7 +335,7 @@ if __name__ == "__main__":
- 至少 2 块 NVIDIA GPU，CUDA 12.8 或更高。
- 根据硬件调整配置文件（[config.yaml](./config.yaml)）。
- 按 Trinity-RFT [安装指南](https://modelscope.github.io/Trinity-RFT/zh/main/tutorial/trinity_installation.html) 从源码安装最新版。
- 按 Trinity-RFT [安装指南](https://agentscope-ai.github.io/Trinity-RFT/zh/main/tutorial/trinity_installation.html) 从源码安装最新版。
- 下载 GSM8K 数据集和 Qwen/Qwen3-0.6B 模型权重（示例）：
```bash

2
tuner/math_agent/config.yaml
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@@ -1,4 +1,4 @@
# Please refer to https://modelscope.github.io/Trinity-RFT/en/main/tutorial/trinity_configs.html for detailed explanation of each field.
# Please refer to https://agentscope-ai.github.io/Trinity-RFT/en/main/tutorial/trinity_configs.html for detailed explanation of each field.
project: AgentScope
name: GSM8K-Qwen3-0.6B
# directory to save checkpoints, default to ./checkpoints if TRINITY_CHECKPOINT_ROOT_DIR not set